[1]刘大瑾,叶建兵,刘家骏.SSIM框架下基于SVD的灰度图像质量评价算法研究[J].南京师范大学学报(自然科学版),2017,40(01):73.[doi:10.3969/j.issn.1001-4616.2017.01.011]
 Liu Dajin,Ye Jianbing,Liu Jiajun.SVD-Based Gray-Scale Image Quality AssessmentAlgorithms in the SSIM Perspective[J].Journal of Nanjing Normal University(Natural Science Edition),2017,40(01):73.[doi:10.3969/j.issn.1001-4616.2017.01.011]
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SSIM框架下基于SVD的灰度图像质量评价算法研究()
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《南京师范大学学报》(自然科学版)[ISSN:1001-4616/CN:32-1239/N]

卷:
第40卷
期数:
2017年01期
页码:
73
栏目:
·数学与计算机科学·
出版日期:
2017-03-31

文章信息/Info

Title:
SVD-Based Gray-Scale Image Quality AssessmentAlgorithms in the SSIM Perspective
文章编号:
1001-4616(2017)01-0073-06
作者:
刘大瑾叶建兵刘家骏
南京理工大学泰州科技学院,江苏 泰州 225300
Author(s):
Liu DajinYe JianbingLiu Jiajun
Taizhou Institute of Science and Technology,Nanjing University of Science and Technology,Taizhou 225300,China
关键词:
图像质量评价奇异值分解结构相似
Keywords:
image quality assessmentsingular value decompositionstructural similarity
分类号:
TP391.41
DOI:
10.3969/j.issn.1001-4616.2017.01.011
文献标志码:
A
摘要:
图像质量评价算法是图像处理研究中的基本问题. 深入讨论图像奇异值分解的性质及基于结构相似性的图像质量评价框架,从理论和实验两方面指出两类算法存在错误评价的问题,并从结构相似的观点出发解释了基于奇异值分解的图像质量评价算法,提出了改进算法的思路.
Abstract:
Image quality assessment is a fundamental problem in the field of image processing. Singular value decomposition properties for images and structural similarity-based image quality assessment are deeply discussed. According to both the theoretical and empirical analysis,the drawbacks of current two categories of algorithms are pointed out. Image quality assessment algorithms that based on singular value decomposition are explained from the perspective of the structural similarity. In addition,possible improvement strategies for the current methods are also discussed.

参考文献/References:

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相似文献/References:

[1]聂守平,魏晓燕.数字图像的奇异值分解[J].南京师范大学学报(自然科学版),2001,24(01):59.
 Nie Shouping,Wei Xiaoyan.Singular Value Decomposition of Digital Image[J].Journal of Nanjing Normal University(Natural Science Edition),2001,24(01):59.

备注/Memo

备注/Memo:
收稿日期:2016-08-20.
基金项目:江苏省高校自然科学研究面上项目(14KJD110004).
通讯联系人:刘大瑾,副教授,研究方向:应用数学. E-mail:54819791@qq.com
更新日期/Last Update: 1900-01-01